Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5207-2024
https://doi.org/10.5194/essd-16-5207-2024
Data description paper
 | 
12 Nov 2024
Data description paper |  | 12 Nov 2024

CIrrMap250: annual maps of China's irrigated cropland from 2000 to 2020 developed through multisource data integration

Ling Zhang, Yanhua Xie, Xiufang Zhu, Qimin Ma, and Luca Brocca

Related authors

Simulating impact of over-grazing on grassland degradation using GIS: a case study in the Heihe River Basin, China
Bingyu Wang, Takashi Oguchi, and Lin Zhang
Abstr. Int. Cartogr. Assoc., 1, 389, https://doi.org/10.5194/ica-abs-1-389-2019,https://doi.org/10.5194/ica-abs-1-389-2019, 2019

Related subject area

Domain: ESSD – Land | Subject: Hydrology
CAMELS-IND: hydrometeorological time series and catchment attributes for 228 catchments in Peninsular India
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam, Pradeep P. Mujumdar, and Ashutosh Sharma
Earth Syst. Sci. Data, 17, 461–491, https://doi.org/10.5194/essd-17-461-2025,https://doi.org/10.5194/essd-17-461-2025, 2025
Short summary
HERA: a high-resolution pan-European hydrological reanalysis (1951–2020)
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025,https://doi.org/10.5194/essd-17-293-2025, 2025
Short summary
BCUB – a large-sample ungauged basin attribute dataset for British Columbia, Canada
Daniel Kovacek and Steven Weijs
Earth Syst. Sci. Data, 17, 259–275, https://doi.org/10.5194/essd-17-259-2025,https://doi.org/10.5194/essd-17-259-2025, 2025
Short summary
Lena River biogeochemistry captured by a 4.5-year high-frequency sampling program
Bennet Juhls, Anne Morgenstern, Jens Hölemann, Antje Eulenburg, Birgit Heim, Frederieke Miesner, Hendrik Grotheer, Gesine Mollenhauer, Hanno Meyer, Ephraim Erkens, Felica Yara Gehde, Sofia Antonova, Sergey Chalov, Maria Tereshina, Oxana Erina, Evgeniya Fingert, Ekaterina Abramova, Tina Sanders, Liudmila Lebedeva, Nikolai Torgovkin, Georgii Maksimov, Vasily Povazhnyi, Rafael Gonçalves-Araujo, Urban Wünsch, Antonina Chetverova, Sophie Opfergelt, and Pier Paul Overduin
Earth Syst. Sci. Data, 17, 1–28, https://doi.org/10.5194/essd-17-1-2025,https://doi.org/10.5194/essd-17-1-2025, 2025
Short summary
CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany
Ralf Loritz, Alexander Dolich, Eduardo Acuña Espinoza, Pia Ebeling, Björn Guse, Jonas Götte, Sibylle K. Hassler, Corina Hauffe, Ingo Heidbüchel, Jens Kiesel, Mirko Mälicke, Hannes Müller-Thomy, Michael Stölzle, and Larisa Tarasova
Earth Syst. Sci. Data, 16, 5625–5642, https://doi.org/10.5194/essd-16-5625-2024,https://doi.org/10.5194/essd-16-5625-2024, 2024
Short summary

Cited articles

Ambika, A. K., Wardlow, B., and Mishra, V.: Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015, Scientific Data, 3, 160118, https://doi.org/10.1038/sdata.2016.118, 2016. 
Bai, M., Zhou, S., and Tang, T.: A Reconstruction of Irrigated Cropland Extent in China from 2000 to 2019 Using the Synergy of Statistics and Satellite-Based Datasets, Land, 11, 1686, https://doi.org/10.3390/land11101686, 2022. 
Bhattarai, N., Lobell, D. B., Balwinder, S., Fishman, R., Kustas, W. P., Pokhrel, Y., and Jain, M.: Warming temperatures exacerbate groundwater depletion rates in India, Science Advance, 9, eadi1401, https://doi.org/10.1126/sciadv.adi1401, 2023. 
Breiman, L.: Random Forests, Machine Learning, 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001. 
Chen, F., Zhao, H., Roberts, D., Van de Voorde, T., Batelaan, O., Fan, T., and Xu, W.: Mapping center pivot irrigation systems in global arid regions using instance segmentation and analyzing their spatial relationship with freshwater resources, Remote Sens. Environ., 297, 113760, https://doi.org/10.1016/j.rse.2023.113760, 2023. 
Download
Short summary
This study presented new annual maps of irrigated cropland in China from 2000 to 2020 (CIrrMap250). These maps were developed by integrating remote sensing data, irrigation statistics and surveys, and an irrigation suitability map. CIrrMap250 achieved high accuracy and outperformed currently available products. The new irrigation maps revealed a clear expansion of China’s irrigation area, with the majority (61%) occurring in the water-unsustainable regions facing severe to extreme water stress.
Share
Altmetrics
Final-revised paper
Preprint